Vision
OpenHands’ vision is to become the open standard for AI coding agents — a foundation for AI software development that is transparent, extensible, and community-driven.Problems We Solve
”Building With” OpenHands: Use OpenHands as an Inner Loop local AI coding agent
Problem: Developers need a reliable and powerful AI coding agent to boost productivity.- Designed for most individual developers
- Ad-hoc usage focused on local or small-team development
- Solves developer productivity challenges
- Provides model-agnostic AI code assistance that integrates locally
- Operates in a highly competitive landscape with multiple alternatives
”Building On” OpenHands: Use OpenHands to solve repetitive engineering tasks
Problem: Organizations need a way to reduce the toil and burden of recurring engineering tasks that distract from roadmap; and they seek solutions that can be scaled to nearly every development team in the organization.- Designed for teams and organizations — these tend to be Commercial entities
- Within organizations, used by Agent Engineers who build agents with OpenHands
- Supports repeatable, cloud-based workflows and automations. Sometimes this is referred to as “Outer Loop” engineering tasks, such as PR reviews, security remediation, and documentation updates.
- Enables API-driven integration into applications and development pipelines
- Solves problems around scalability, extensibility, and control
- Focused on enabling custom agent orchestration
Example Use Cases — Repetitive Engineering Tasks
OpenHands is used across a wide range of powerful, scalable use-cases in the SDLC process:- Maintenance
- Example: 30x throughput on CVE resolution
- Example: Automatic documentation and release notes
- Modernization
- Example: Adding type annotations to an entire Python codebase
- Example: Refactoring a monolithic Java application to microservices
- Migration
- Example: Upgrading 1000s of jobs from Spark 2 to Spark 3
- Example: Moving from Redux to Zustand
- Tech Debt
- Example: Detecting and deleting unused code
- Example: Adding error handling based on production logs
- Automated Testing, Bug Fixing, Documentation, etc.
Target Customers for OSS and Commercial
Open Source (OSS)
- Goal: Empower individual developers with a model-agnostic, open, and extensible coding agent that integrates seamlessly into their workflows.
- Primary audience: Individual developers on the bleeding edge of software development; AI hobbyists.
- Use cases: Personal productivity, ad-hoc local development, experimentation, and contributing to open AI infrastructure.
Commercial
- Primary audience: Mid-to-large enterprises and technical teams.
- Goal: Help organizations safely leverage AI at scale to modernize, refactor, and maintain complex systems across 100s of development teams.
- User personas:
- Developers w/ AI experience: Developers who already may be familiar with pairing with AI to accomplish work, but ready to begin delegating wholesale tasks to AI agents for maximum productivity.
- Agent Engineers: Developers on the edge of AI engineering who are looking to integrate agents into workflows or applications.
- Buyer personas: Engineering Leaders
- Use cases:
- “An OpenHands agent for every developer”: Multi-user collaboration, scalability, governance, and security
- Refactoring and code modernization
- Embedding AI agents into apps and workflows
Dividing Lines Between OSS and Commercial
OpenHands’ CEO and founder discusses the lines between OSS and Commercial in this blog post: Walking the Line with Commercial Open Source (June 2025) OpenHands follows an Open Core model:- Open Source Core: The foundation of OpenHands is open and free for all developers. Most new features default to open source unless they explicitly solve enterprise-specific needs.
- Enterprise Offering: Focused on mid-to-large enterprises, addressing needs around multi-user management, scalability, and security.
Feature Selection Principle
- Developer problems → Open source by default: Features that solve an individual developer’s needs belong in the open source core (e.g., productivity, model integration, developer tooling).
- Buyer problems → Commercial features: Features designed to solve organizational or managerial challenges are commercial (e.g., organizational management, collaboration, scalability).
- Commercial feature: Organizational Management — features for managing OpenHands access across hundreds of developers
- Open Source: MCP support, Secrets Support, Planning Agent mode, etc.
Strategic Challenges
- Large Product Portfolio Balancing focus and resources across a broad range of features and use cases.
- Driving More Community Contributions Encouraging external contributors while maintaining code quality and stewardship.
- Increasingly Crowded “Build With” Market: Differentiating in a competitive field of AI coding assistants.
- Wide-Ranging Developer Profiles: Supporting diverse users — from new-to-AI developers to hobbyists to enterprise teams.
Unique Differentiators
- Open Source Foundation: Transparent, extensible, and community-driven.
- Model-Agnostic Architecture: Works with any LLM — the durable value lies in the agent layer, not the model.
- Cloud-First Scalability: Supports persistent, autonomous cloud agents that can handle repetitive, large-scale tasks.
- Focus on Repetitive Tasks: Automates ongoing engineering work — refactoring, maintenance, dependency upgrades — where AI delivers compounding value.
- Dual Persona Alignment: Serves both individual developers (“Build With”) and enterprise teams (“Build On”) through a unified ecosystem.
Strategic Roadmap Pillars
- Bet on Cloud Agents as the best way to work with AI coding agents Prioritize cloud-based runtimes for scalable, persistent, autonomous systems.
- Shifting towards “Build On” to optimize for repetitive, high-leverage work Emphasize ongoing tasks like maintenance and refactoring over one-off code generation.
- Maintain a high performance, model-agnostic approach Continue to integrate multiple models and support extensibility as the LLM ecosystem evolves.
- Bridge both developer needs and enterprise needs Build pathways that help individual developers grow into organizational adopters — “Build With” → “Build On.”
- Foster a thriving Open Source community Grow contributor engagement, maintain transparent governance, and accelerate open development.
Commitment to Open Source
We believe open source works best with clear stewardship and active participation.- We maintain the roadmap and good first issues to guide community contributions.
- We review pull requests diligently and recognize valuable contributions.
- We maintain transparent metrics across:
- Community: Total contributors and open PRs awaiting review.
- Product Quality: NPS and SaaS adoption as a proxy for user satisfaction.
- Adoption: Public reference examples and tutorials.
- Impact: Case studies highlighting enterprise deployments.